À propos de ce cours
4.7
2,536 notes
571 avis
Spécialisation
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100 % en ligne

Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Dates limites flexibles

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Réinitialisez les dates limites selon votre disponibilité.
Niveau débutant

Niveau débutant

Heures pour terminer

Approx. 21 heures pour terminer

Recommandé : 5 weeks of study, 5-7 hours/week...
Langues disponibles

Anglais

Sous-titres : Anglais, Coréen...

Compétences que vous acquerrez

StatisticsR ProgrammingRstudioExploratory Data Analysis
Spécialisation
100 % en ligne

100 % en ligne

Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Dates limites flexibles

Dates limites flexibles

Réinitialisez les dates limites selon votre disponibilité.
Niveau débutant

Niveau débutant

Heures pour terminer

Approx. 21 heures pour terminer

Recommandé : 5 weeks of study, 5-7 hours/week...
Langues disponibles

Anglais

Sous-titres : Anglais, Coréen...

Programme du cours : ce que vous apprendrez dans ce cours

Semaine
1
Heures pour terminer
12 minutes pour terminer

About Introduction to Probability and Data

<p>This course introduces you to sampling and exploring data, as well as basic probability theory. You will examine various types of sampling methods and discuss how such methods can impact the utility of a data analysis. The concepts in this module will serve as building blocks for our later courses.<p>Each lesson comes with a set of learning objectives that will be covered in a series of short videos. Supplementary readings and practice problems will also be suggested from <a href="https://leanpub.com/openintro-statistics/" target="_blank">OpenIntro Statistics, 3rd Edition</a> (a free online introductory statistics textbook, that I co-authored). There will be weekly quizzes designed to assess your learning and mastery of the material covered that week in the videos. In addition, each week will also feature a lab assignment, in which you will use R to apply what you are learning to real data. There will also be a data analysis project designed to enable you to answer research questions of your own choosing.<p>Since this is a Coursera course, you are welcome to participate as much or as little as you’d like, though I hope that you will begin by participating fully. One of the most rewarding aspects of a Coursera course is participation in forum discussions about the course materials. Please take advantage of other students' feedback and insight and contribute your own perspective where you see fit to do so. You can also check out the <a href="https://www.coursera.org/learn/probability-intro/resources/crMc4" target="_blank">resource page</a> listing useful resources for this course. <p>Thank you for joining the Introduction to Probability and Data community! Say hello in the Discussion Forums. We are looking forward to your participation in the course.</p>...
Reading
1 vidéo (Total 2 min), 1 lecture
Reading1 lecture
More about Introduction to Probability and Data10 min
Heures pour terminer
2 heures pour terminer

Introduction to Data

<p>Welcome to Introduction to Probability and Data! I hope you are just as excited about this course as I am! In the next five weeks, we will learn about designing studies, explore data via numerical summaries and visualizations, and learn about rules of probability and commonly used probability distributions. If you have any questions, feel free to post them on <a href="https://www.coursera.org/learn/probability-intro/module/rQ9Al/discussions?sort=lastActivityAtDesc&page=1" target="_blank"><b>this module's forum</b></a> and discuss with your peers! To get started, view the <a href="https://www.coursera.org/learn/probability-intro/supplement/rooeY/lesson-learning-objectives" target="_blank"><b>learning objectives</b></a> of Lesson 1 in this module.</p>...
Reading
7 vidéos (Total 30 min), 5 lectures, 3 quiz
Video7 vidéos
Data Basics5 min
Observational Studies & Experiments4 min
Sampling and sources of bias8 min
Experimental Design2 min
(Spotlight) Random Sample Assignment3 min
DataCamp Instructions2 min
Reading5 lectures
Lesson Learning Objectives10 min
Suggested Readings and Practice10 min
About Lesson Choices (Read Before Selection)10 min
Week 1 Lab Instructions (RStudio)10 min
Week 1 Lab Instructions (DataCamp)10 min
Quiz3 exercices pour s'entraîner
Week 1 Practice Quiz10 min
Week 1 Quiz14 min
Week 1 Lab: Introduction to R and RStudio16 min
Semaine
2
Heures pour terminer
3 heures pour terminer

Exploratory Data Analysis and Introduction to Inference

<p>Welcome to Week 2 of Introduction to Probability and Data! Hope you enjoyed materials from Week 1. This week we will delve into numerical and categorical data in more depth, and introduce inference. </p>...
Reading
7 vidéos (Total 46 min), 5 lectures, 3 quiz
Video7 vidéos
Measures of Center4 min
Measures of Spread6 min
Robust Statistics1 min
Transforming Data3 min
Exploring Categorical Variables8 min
Introduction to Inference12 min
Reading5 lectures
Lesson Learning Objectives10 min
Lesson Learning Objectives10 min
Suggested Readings and Practice10 min
Week 2 Lab Instructions (RStudio)10 min
Week 2 Lab Instructions (DataCamp)10 min
Quiz3 exercices pour s'entraîner
Week 2 Practice Quiz10 min
Week 2 Quiz12 min
Week 2 Lab: Introduction to Data20 min
Semaine
3
Heures pour terminer
3 heures pour terminer

Introduction to Probability

<p>Welcome to Week 3 of Introduction to Probability and Data! Last week we explored numerical and categorical data. This week we will discuss probability, conditional probability, the Bayes’ theorem, and provide a light introduction to Bayesian inference. </p><p>Thank you for your enthusiasm and participation, and have a great week! I’m looking forward to working with you on the rest of this course. </p>...
Reading
9 vidéos (Total 82 min), 5 lectures, 3 quiz
Video9 vidéos
Disjoint Events + General Addition Rule9 min
Independence9 min
Probability Examples9 min
(Spotlight) Disjoint vs. Independent2 min
Conditional Probability12 min
Probability Trees10 min
Bayesian Inference14 min
Examples of Bayesian Inference7 min
Reading5 lectures
Lesson Learning Objectives10 min
Lesson Learning Objectives10 min
Suggested Readings and Practice10 min
Week 3 Lab Instructions (RStudio)10 min
Week 3 Lab Instructions (DataCamp)10 min
Quiz3 exercices pour s'entraîner
Week 3 Practice Quiz6 min
Week 3 Quiz10 min
Week 3 Lab: Probability10 min
Semaine
4
Heures pour terminer
2 heures pour terminer

Probability Distributions

<p>Great work so far! Welcome to Week 4 -- the last content week of Introduction to Probability and Data! This week we will introduce two probability distributions: the normal and the binomial distributions in particular. As usual, you can evaluate your knowledge in this week's quiz. There will be <b>no labs</b> for this week. Please don't hesitate to post any questions, discussions and related topics on <a href="https://www.coursera.org/learn/probability-intro/module/VdVNg/discussions?sort=lastActivityAtDesc&page=1" target="_blank"><b>this week's forum</b></a>.</p>...
Reading
6 vidéos (Total 67 min), 4 lectures, 2 quiz
Video6 vidéos
Evaluating the Normal Distribution2 min
Working with the Normal Distribution5 min
Binomial Distribution17 min
Normal Approximation to Binomial14 min
Working with the Binomial Distribution9 min
Reading4 lectures
Lesson Learning Objectives10 min
Lesson Learning Objectives10 min
Suggested Readings and Practice10 min
Data Analysis Project Example10 min
Quiz2 exercices pour s'entraîner
Week 4 Practice Quiz14 min
Week 4 Quiz14 min
4.7
571 avisChevron Right
Orientation de carrière

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a commencé une nouvelle carrière après avoir terminé ces cours
Avantage de carrière

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Meilleurs avis

par AAJan 24th 2018

This course literally taught me a lot, the concepts were beautifully explained but the way it was delivered and overall exercises and the difficulty of problems made it more challenging and enjoying.

par HDMar 31st 2018

The tutor makes it really simple. The given examples really helped to understand the concepts and apply it to a wide range of problems. Thank you for this. Wish I could complete the assignments too.

Enseignant

Avatar

Mine Çetinkaya-Rundel

Associate Professor of the Practice
Department of Statistical Science

À propos de Duke University

Duke University has about 13,000 undergraduate and graduate students and a world-class faculty helping to expand the frontiers of knowledge. The university has a strong commitment to applying knowledge in service to society, both near its North Carolina campus and around the world....

À propos de la Spécialisation Statistics with R

In this Specialization, you will learn to analyze and visualize data in R and create reproducible data analysis reports, demonstrate a conceptual understanding of the unified nature of statistical inference, perform frequentist and Bayesian statistical inference and modeling to understand natural phenomena and make data-based decisions, communicate statistical results correctly, effectively, and in context without relying on statistical jargon, critique data-based claims and evaluated data-based decisions, and wrangle and visualize data with R packages for data analysis. You will produce a portfolio of data analysis projects from the Specialization that demonstrates mastery of statistical data analysis from exploratory analysis to inference to modeling, suitable for applying for statistical analysis or data scientist positions....
Statistics with R

Foire Aux Questions

  • Une fois que vous êtes inscrit(e) pour un Certificat, vous pouvez accéder à toutes les vidéos de cours, et à tous les quiz et exercices de programmation (le cas échéant). Vous pouvez soumettre des devoirs à examiner par vos pairs et en examiner vous-même uniquement après le début de votre session. Si vous préférez explorer le cours sans l'acheter, vous ne serez peut-être pas en mesure d'accéder à certains devoirs.

  • Lorsque vous vous inscrivez au cours, vous bénéficiez d'un accès à tous les cours de la Spécialisation, et vous obtenez un Certificat lorsque vous avez réussi. Votre Certificat électronique est alors ajouté à votre page Accomplissements. À partir de cette page, vous pouvez imprimer votre Certificat ou l'ajouter à votre profil LinkedIn. Si vous souhaitez seulement lire et visualiser le contenu du cours, vous pouvez accéder gratuitement au cours en tant qu'auditeur libre.

  • No. Completion of a Coursera course does not earn you academic credit from Duke; therefore, Duke is not able to provide you with a university transcript. However, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

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